ML Engineer for Materials Discovery (MLIPs)

ML Engineer for Materials Discovery (MLIPs)

Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
J

At a Glance

  • Tasks: Lead the development of machine learning interatomic potentials and design scalable ML pipelines.
  • Company: Jack & Jill, a pioneering company in materials discovery based in London.
  • Benefits: Hybrid work environment, competitive salary, and opportunities for real-world impact.
  • Other info: Collaborate with physics teams and enjoy excellent career growth opportunities.
  • Why this job: Blend theory and experiment to influence groundbreaking materials research.
  • Qualifications: Experience with machine learning frameworks like PyTorch or JAX.

The predicted salary is between 60000 - 80000 £ per year.

Jack & Jill in London, UK, is seeking a Machine Learning Engineer to lead the development of machine learning interatomic potentials (MLIPs).

You will design scalable ML pipelines, train models with Py Torch or JAX, and collaborate with physics teams to build high-quality DFT-derived datasets.

The role blends theory and experiment, bridging computational research with a physical laboratory, and offers a hybrid work environment with opportunities to influence real-world materials discovery.

#J-18808-Ljbffr

ML Engineer for Materials Discovery (MLIPs) employer: Jack & Jill

At Jack & Jill, we pride ourselves on being an exceptional employer that fosters a dynamic and innovative work culture. Our team enjoys a range of benefits including flexible working arrangements, professional development opportunities, and a collaborative environment that encourages creativity and growth. Located in a vibrant area, we offer unique advantages such as access to cutting-edge technology and the chance to work with industry leaders in AI-driven marketing strategies.

J

Contact Details:

Jack & Jill Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land ML Engineer for Materials Discovery (MLIPs)

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Jack & Jill!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like ML Engineer for Materials Discovery (MLIPs) at Jack & Jill.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Jack & Jill.

Apply Directly through Our Website

When you find a suitable opening like ML Engineer for Materials Discovery (MLIPs) at Jack & Jill, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace ML Engineer for Materials Discovery (MLIPs)

Machine Learning
Interatomic Potentials
ML Pipelines
PyTorch
JAX
Data Analysis
Collaboration

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Jack & Jill, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Jack & Jill. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Jack & Jill

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Jack & Jill!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.